{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 第二次作业"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Cqar2/fffR9x1110H586dG156X3p6ul9wcHC1WkxSm2mUOseMMfki8glW0JgLRBljltr7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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e84b71aef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "df = pd.read_csv('OutOrder.csv', encoding='gbk')\n",
    "df[\"订单ID\"] = df[\"订单ID\"].astype(object)\n",
    "df['时间'] = pd.to_datetime(df['时间'])\n",
    "df['日期'] = df.apply(lambda row: row['时间'].date(), axis=1)\n",
    "df['年月'] = df.apply(lambda row: row['日期'].isoformat()[0:7], axis=1)\n",
    "\n",
    "# 筛选排序\n",
    "# df2 = df[df['方式'].str.contains('网')].head().sort_values(by=['方式','日期'],ascending=[0,1]).ix[:,[2,4,1]]\n",
    "\n",
    "fig = plt.figure(figsize=(9, 10))\n",
    "\n",
    "ax0 = fig.add_subplot('411')\n",
    "ax1 = fig.add_subplot('412')\n",
    "ax2 = fig.add_subplot('413')\n",
    "ax3 = fig.add_subplot('414')\n",
    "\n",
    "group_type = df.groupby('方式')['金额'].sum().sort_values(ascending=False)\n",
    "explode = np.zeros(len(group_type.index))\n",
    "explode[0] = 0.05\n",
    "ax0.pie(group_type, autopct='%3.1f%%', labels=group_type.index, startangle=0, explode=explode)\n",
    "ax0.axis('equal')\n",
    "ax0.legend()\n",
    "ax0.set_title('支付方式分布图')\n",
    "\n",
    "group_ym = df.groupby('年月')['金额'].sum().sort_index()\n",
    "X = np.arange(len(group_ym.index))\n",
    "Y = group_ym.values\n",
    "ax1.bar(X, Y, )\n",
    "ax1.plot(X, Y,'r')\n",
    "ax1.plot(X, Y,'ro')\n",
    "ax1.set_xticks(X)\n",
    "ax1.set_xticklabels(group_ym.index)\n",
    "ax1.set_title('各月份金额增长趋势')\n",
    "for x, y in zip(X, Y):\n",
    "    ax1.text(x, y+300, '%.2f'%y, ha='center', va='bottom')\n",
    "ax1.set_ylim(0, 5000)\n",
    "\n",
    "group_date = df.groupby('日期')['金额'].sum().sort_index()\n",
    "X = np.arange(len(group_date.index))\n",
    "Y = group_date.values\n",
    "ax2.plot(X,Y)\n",
    "# ax2.set_xticks(X)\n",
    "# ax2.set_xticklabels(group_date.index)\n",
    "\n",
    "\n",
    "#用户增长趋势分析，按天\n",
    "N = 1 #设置分布宽度\n",
    "date_list = df['日期'].tolist()\n",
    "#修改了上次的错误，用最大日期减去最小日期之间的天数+1作为bins的参数\n",
    "ax3.hist(date_list, bins=int((max(date_list) - min(date_list)).days)+1, normed=0, histtype='bar', facecolor='g', alpha=1)\n",
    "ax3.set_title('用户数量增长情况-按天')\n",
    "\n",
    "fig.subplots_adjust(hspace=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>方式</th>\n",
       "      <th>日期</th>\n",
       "      <th>金额</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>网银</td>\n",
       "      <td>2015-07-15</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>网银</td>\n",
       "      <td>2015-08-06</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>网银</td>\n",
       "      <td>2015-08-13</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>网银</td>\n",
       "      <td>2015-10-20</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>网易宝</td>\n",
       "      <td>2015-07-21</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      方式          日期    金额\n",
       "164   网银  2015-07-15  10.0\n",
       "101   网银  2015-08-06  15.0\n",
       "88    网银  2015-08-13  15.0\n",
       "232   网银  2015-10-20  18.0\n",
       "142  网易宝  2015-07-21  10.0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "df = pd.read_csv('OutOrder.csv', encoding='gbk')\n",
    "df['订单ID'] = df['订单ID'].astype(object)\n",
    "df['时间'] = pd.to_datetime(df['时间'])\n",
    "df['日期'] = df.apply(lambda row: row['时间'].date(), axis=1)\n",
    "df['年月'] = df.apply(lambda row: row['日期'].isoformat()[0:7], axis=1)\n",
    "# df = df.sort_values('时间')\n",
    "# df2 = df.set_index('时间')\n",
    "# df2['20151001':'20151031'].head()\n",
    "df2 = df[df['方式'].str.contains('网')].head().sort_values(by=['方式','日期'],ascending=[0,1]).ix[:,[2,4,1]]\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6    232\n",
      "5    209\n",
      "3    205\n",
      "4    128\n",
      "2    107\n",
      "1     72\n",
      "Name: year-month-No, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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kY5KNmzdvHtFmJUnSYjGq0PGJJPskuT3wGOArUxeoqvVVtaaq1kxM2M9UkqSdzaiGQT8R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\nv0vnA2cC0+nxOMBjP6ffMNLr10Oto+jxGDBMreNp+RjQ9r9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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e849950940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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xOyK+VVr27YiYFRGfq2ZtkiRp4Kp2D8w5wC0ppalAY0RcAhRSStOA10TE5OqW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\nYCRJUnMMMJIkqTkGGEmS1Jz/H88SkaQSE1fRAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e84add8dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "import os\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "#设置美化格式\n",
    "# plt.style.use('bmh')\n",
    "\n",
    "#星期字典\n",
    "week_dict = {1:'星期一', 2:'星期二', 3:'星期三', 4:'星期四', 5:'星期五', 6:'星期六', 7:'星期日'}\n",
    "\n",
    "#将文件读到dataframe中\n",
    "def readOrders(file_name): \n",
    "    data = pd.read_csv(file_name, encoding='gbk')\n",
    "    #修改列名为英文\n",
    "    data = data.rename(columns={'订单ID': 'id', '金额': 'money','方式': 'channel','时间':'time'})\n",
    "\n",
    "    #从字符串得到日期类型\n",
    "    #时间格式(包括日期和时间)\n",
    "    time_str = '%m/%d/%Y %H:%M'\n",
    "    data['datetime'] = data.apply(lambda row: datetime.strptime(row['time'], time_str), axis=1)\n",
    "\n",
    "    #时间格式,只有时间\n",
    "    data['date'] = data.apply(lambda row: row['datetime'].date(), axis=1)\n",
    "\n",
    "    #月份，这个有问题，查了很久解决不了，目前只在2015年能用，不知道如何在2016年将年份区别开\n",
    "    #data['month'] = data.apply(lambda row: row['datetime'].month, axis=1)\n",
    "\n",
    "    #增加了老师提供的方法，将年和月作为index\n",
    "    data['year-month'] = data.apply(lambda row: row['datetime'].isoformat()[0:7], axis=1)\n",
    "    #print(data['year-month'])\n",
    "\n",
    "    #year-month排序后的序号，这样才能在bar中画图\n",
    "    #得到data['year-month']中的set\n",
    "    sorted_year_month_list = sorted(set(data['year-month'].tolist()), reverse=False)\n",
    "    #print(sorted_year_month_list)\n",
    "    #年-月组成的字符串排序后放入字典，以便后面使用\n",
    "    year_month_No_dict = {}\n",
    "    num = 1\n",
    "    for year_month in sorted_year_month_list:\n",
    "        year_month_No_dict[year_month] = num\n",
    "        num += 1\n",
    "    data['year-month-No'] = data.apply(lambda row: year_month_No_dict[row['year-month']], axis=1)\n",
    "\n",
    "    #增加星期列，数字\n",
    "    data['week_id'] = data.apply(lambda row: row['datetime'].weekday()+1, axis=1)\n",
    "    #增加星期列，名称\n",
    "    data['week_name'] = data.apply(lambda row: week_dict[row['week_id']], axis=1)\n",
    "\n",
    "    #小时，几点\n",
    "    data['hour'] = data.apply(lambda row: row['datetime'].hour, axis=1)\n",
    "\n",
    "    #返回结果按照时间排序\n",
    "    return data\n",
    "\n",
    "\n",
    "#用户分析\n",
    "def userAnalysis(data):\n",
    "\n",
    "    fig = plt.figure(figsize=(9,20))#figsize=(10,6)\n",
    "\n",
    "    #行, 列, 序号\n",
    "    ax0 = fig.add_subplot(311) \n",
    "    ax1 = fig.add_subplot(323)\n",
    "    ax2 = fig.add_subplot(324)\n",
    "    ax3 = fig.add_subplot(313)\n",
    "\n",
    "    #用户增长趋势分析，按天\n",
    "    N = 1 #设置分布宽度\n",
    "    date_list = data['date'].tolist()\n",
    "    #修改了上次的错误，用最大日期减去最小日期之间的天数+1作为bins的参数\n",
    "    ax0.hist(date_list, bins=int((max(date_list) - min(date_list)).days)+1, normed=0, histtype='bar', facecolor='g', alpha=1)\n",
    "    ax0.set_title('用户数量增长情况-按天')\n",
    "\n",
    "\n",
    "    #用户在星期上的分布\n",
    "    week_count = data['week_id'].value_counts()\n",
    "\n",
    "    ax1.bar(week_count.index.values.tolist(),week_count.values.tolist(),align=\"center\")\n",
    "    ax1.set_xticks(list(range(1,8)))\n",
    "    ax1.set_xticklabels(week_dict.values())\n",
    "    ax1.set_title('用户在星期上的分布')\n",
    "\n",
    "    #用户在月份上的分布\n",
    "    month_count = data['year-month-No'].value_counts()\n",
    "    print(month_count)\n",
    "    ax2.bar(month_count.index.values.tolist(),month_count.values.tolist(),align=\"center\")\n",
    "    ax2.set_xticks(range(min(data['year-month-No']), max(data['year-month-No'])+1))\n",
    "    ax2.set_xticklabels(sorted(set(data['year-month'].tolist()), reverse=False))\n",
    "\n",
    "    ax2.set_title('用户在月份上的分布')\n",
    "\n",
    "    #用户在每天时间段上的分布\n",
    "    hour_count = data['hour'].value_counts()\n",
    "    ax3.bar(hour_count.index.values.tolist(),hour_count.values.tolist())\n",
    "    ax3.set_xticks(list(range(0,24)))\n",
    "\n",
    "    data['year-month']\n",
    "    ax3.set_title('用户在一天内时间段的分布')\n",
    "\n",
    "\n",
    "    fig.subplots_adjust(hspace=0.7)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "#价格收入等分析\n",
    "def moneyAnalysis(data):\n",
    "    import matplotlib.cm as cm\n",
    "    import itertools\n",
    "\n",
    "    fig = plt.figure(figsize=(9,20))#figsize=(10,6)\n",
    "\n",
    "    #行, 列, 序号\n",
    "    ax0 = fig.add_subplot(211) \n",
    "    ax1 = fig.add_subplot(212)\n",
    "\n",
    "\n",
    "    #不同支付方式在不同时间的价格变化\n",
    "    channels = set(data['channel'].tolist())\n",
    "    #生成颜色列表\n",
    "    colors =   iter(cm.rainbow(np.linspace(0, 1, len(channels))))\n",
    "    for channel in channels:\n",
    "        date_list = data[data['channel']==channel]['datetime'].tolist()\n",
    "        money_list = data[data['channel']==channel]['money'].tolist()\n",
    "        ax0.scatter(date_list,money_list,label=channel,s=5,color=next(colors))\n",
    "    ax0.legend()\n",
    "    ax0.set_title('不同支付方式在不同时间的交易金额变化')\n",
    "    ax0.set_ylabel(u'金额  单位：元')\n",
    "    ax0.set_xlabel(u'时间')\n",
    "\n",
    "\n",
    "\n",
    "    #收入在月份上的变化\n",
    "    money_month = data.groupby('year-month-No').sum()['money']\n",
    "    #将money除以1000\n",
    "    monty_month_value = [x/10  for x in money_month.values.tolist()]\n",
    "    ax1.bar(money_month.index.values.tolist(),monty_month_value,facecolor='#9999ff',align=\"center\")\n",
    "\n",
    "    #用户在月份上的分布\n",
    "    month_count = data['year-month-No'].value_counts()\n",
    "    #将数据变为负数\n",
    "    neg_month_count = [-x for x in month_count.values.tolist()]\n",
    "    ax1.bar(month_count.index.values.tolist(),neg_month_count, facecolor='#ff9999',align=\"center\")\n",
    "    ax1.set_xticks(range(min(data['year-month-No']), max(data['year-month-No'])+1))\n",
    "    ax1.set_xticklabels(sorted(set(data['year-month'].tolist()), reverse=False))\n",
    "\n",
    "\n",
    "    ax1.set_title('每月收入 (上）以及用户在月份上的分布（下）')\n",
    "    ax1.set_ylabel(u'收入 单位： 十元； 用户单位：个')\n",
    "    ax1.set_xlabel(u'月份')\n",
    "\n",
    "\n",
    "    fig.subplots_adjust(hspace=0.7)\n",
    "    plt.show()\n",
    "\n",
    "if __name__ == '__main__':\n",
    "\n",
    "    data = readOrders('OutOrder.csv')\n",
    "    #用户分析\n",
    "    userAnalysis(data)\n",
    "    moneyAnalysis(data)"
   ]
  }
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